The many forms of beta diversity: a comment on McGill et al. and some notational suggestions
Bibliographic record
Abstract
Fundamentally, beta diversity is a measure of species turnover across time or space. In practice, it is sometimes unclear exactly what aspect of beta diversity that is implied in studies. For instance, a trend in ’spatial beta diversity’ can be used to refer to both differences in spatial beta diversity between sites, as well as a temporal trend in spatial beta diversity (at the same site). In a recent review, McGill et al. [1] provide a useful and much needed overview of different aspects of biodiversity change, and show areas where we lack knowledge. Even so, McGill et al. ignore some aspects of beta diversity and sometimes pool different types of beta diversity under the same heading. However, their review mainly focused on temporal trends in diversity, while I here want to highlight spatial patterns in temporal β -diversity (species turnover) as an important but somewhat overlooked component of biodiversity change. Furthermore, I propose a slightly modified classification and nomenclature of metrics of biodiversity change, with the aim of complementing their review. The notation used here can hopefully be useful to other authors as well.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.131 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.007 | 0.018 |
| Open science | 0.015 | 0.006 |
| Research integrity | 0.030 | 0.056 |
| Insufficient payload (model declined to judge) | 0.012 | 0.016 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".